docstr: Create and return a predictor object.
  
  Returns
  -------
  Predictor
      A predictor wrapping a `nn.Module` used for inference.
docstr_tok: ["Create","and","return","a","predictor","object",".","Returns","--","--","--","-","Predictor","A","predictor","wrapping","a","`","nn.Module","`","used","for","inference","."]
code: def create_predictor(
      self,
      transformation: Transformation,
      trained_network: nn.Module,
      device: torch.device,
  ) -> PyTorchPredictor:
      """
      Create and return a predictor object.
  
      Returns
      -------
      Predictor
          A predictor wrapping a `nn.Module` used for inference.
      """
      raise NotImplementedError
  
imports: from typing import NamedTuple, Optional
  from functools import partial
  import numpy
  import torch
  import torch.nn
  from torch.utils import data
  from torch.utils.data import DataLoader
  from gluonts.env import env
  from gluonts.core.component import validated
  from gluonts.dataset.common import Dataset
  from gluonts.model.estimator import Estimator
  from gluonts.torch.model.predictor import PyTorchPredictor
  from gluonts.transform import SelectFields, Transformation
  from pts import Trainer
  from pts.model import get_module_forward_input_names
  from pts.dataset.loader import TransformedIterableDataset
label_desc: Use image node_id 5 for calling the PyTorchEstimator obj's underlying member method code with example usage: obj.create_predictor(transformation, trained_network, device) without return types